Vehicle Pairing for Privacy-Graded Navigation Sharing
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Solution Overview
Problem
Existing systems face challenges in coordinating navigation-based content, such as destinations and locations, between multiple autonomous or highly-assisted vehicles while ensuring user privacy, especially in scenarios requiring multiple vehicles for ride-sharing trips.
Innovation Solution
A computer-implemented method for privacy-sensitive sharing of navigation-based content between vehicles, involving vehicle pairing, determining privacy levels, and granting access rights to share destination and location information based on these levels, allowing vehicles to follow each other effectively during trips.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If navigation-based content is shared between multiple vehicles to enable coordinated trip completion, then the productivity and ease of operation improve, but user privacy is compromised
Solution Approach 1:
The patent applies local quality by implementing different privacy levels for different types of navigation content. Sensitive information like exact destinations is protected with higher privacy levels, while less sensitive information like general route progress can be shared. This allows selective sharing based on the specific characteristics of each data element, resolving the contradiction between coordination efficiency and privacy protection.
Solution Approach 2:
The patent segments navigation-based content into multiple granularity levels (e.g., destination, route, progress markers). This segmentation enables differential sharing where only necessary portions of navigation data are exchanged between vehicles. By dividing the information hierarchy, the system achieves efficient coordination through shared high-level routing while protecting private destination information, thus resolving the privacy-productivity contradiction.
2Ease of operation
If complete navigation content is shared between vehicles, then the ease of operation improves, but the loss of information increases due to privacy exposure
Solution Approach 1:
The system applies local quality by assigning different privacy protection levels to different components of navigation content. High-level routing information can be freely shared to ease vehicle coordination, while specific destination details maintain higher privacy protection. This selective approach enables operational ease without comprehensive privacy loss.
Solution Approach 2:
The patent implements dynamic privacy control where the granularity of shared information can change based on contextual factors such as trust level between vehicles, trip stage, and user preferences. This dynamic adjustment allows the system to optimize the balance between ease of operation and privacy protection in real-time, sharing more information when coordination is needed and protecting privacy when risks are higher.
3Loss of information
If privacy protection measures are implemented for navigation content sharing, then the loss of information decreases, but the device complexity increases
Solution Approach 1:
The patent implements a universal privacy management framework that handles multiple types of navigation content (destination, route, progress) through a single standardized interface. The privacy level determination mechanism works across different data types and sharing scenarios, reducing the need for separate complex management systems for each case. This multi-functionality approach preserves privacy while minimizing overall system complexity.
Solution Approach 2:
The system performs preliminary privacy level determination and content granularity selection before actual sharing occurs. By pre-configuring privacy parameters and filtering navigation content according to established rules before transmission, the system reduces the complexity of real-time privacy management. This preliminary processing ensures privacy preservation while simplifying the ongoing sharing operations.
Data Source
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AI summary
An approach is provided for privacy-sensitive sharing of navigation-based content between vehicles (e.g., autonomous vehicles, drones, devices, etc.). The approach involves initiating a pairing of a first vehicle with at least one second vehicle. The approach also involves determining a privacy level associated with the pairing. The approach further involves determining a granularity level for sharing the navigation-based content of the first vehicle with the at least one second vehicle based on the privacy level. The approach further involves granting an access right to the at least one second vehicle to access the navigation-based content at the determined granularity level. The at least one second vehicle is then guided based on the navigation-based content of the first vehicle at the determined granularity level.